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Sunalamye

MCP Claude Shell Server

by Sunalamye

claude_generate_json

Generate structured JSON responses from prompts with built-in validation and retry logic for reliable AI-powered outputs.

Instructions

Generate JSON response with validation and retry

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesPrompt to pass to Claude CLI
modelNoModel to use (haiku, sonnet, opus). Default: haiku
maxRetriesNoMaximum retry attempts for JSON validation. Default: 3
jsonSchemaNoJSON Schema to validate output against
systemPromptNoReplace default system prompt
appendSystemPromptNoAppend to default system prompt
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions 'validation and retry', which hints at error handling and retry logic, but doesn't disclose key behavioral traits such as what happens on validation failure (e.g., error messages, retry behavior details), rate limits, authentication needs, or output format specifics. This leaves significant gaps for a tool with validation features.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence: 'Generate JSON response with validation and retry'. It's front-loaded and wastes no words, though it could be slightly more informative. Every word earns its place, making it appropriately concise for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and 6 parameters, the description is incomplete. It doesn't explain the return values (e.g., JSON structure), error handling details, or how validation works with jsonSchema. For a tool focused on JSON generation with validation, more context is needed to understand its full behavior and output.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no additional meaning beyond the schema, such as explaining interactions between parameters (e.g., how jsonSchema relates to validation) or usage examples. Baseline is 3 as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'Generate JSON response with validation and retry', which indicates it generates JSON and includes validation/retry features. However, it doesn't specify what resource or content it generates JSON from (Claude's output), nor does it differentiate from siblings like claude_generate or claude_edit_json. The purpose is somewhat vague about the exact operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like claude_generate (which might generate non-JSON) or claude_edit_json (which might edit existing JSON). The description implies JSON generation with validation, but there's no explicit context or exclusions mentioned for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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